ReviewJornal de pediatria
Face-based automatic pain assessment: challenges and perspectives in neonatal intensive care units.
Review in Jornal de pediatria. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Neonatal pain assessment and non-pharmacological analgesia: an integrative literature review.Frontiers in pain research (Lausanne, Switzerland) · 2026Pooled it
- Ethical aspects of artificial intelligence use in neonatal intensive care units: a scoping review.European journal of pediatrics · 2026Article
- Evaluation of Pain in Infants of the First 100 Days of Age With Artificial Intelligence Techniques.Journal of evaluation in clinical practice · 2026Article
- PANDIA: Personalized neuro-symbolic multimodal fusion for interpretable neonatal pain assessment.PLOS digital health · 2026Article
- Machine learning classification of EEG responses to pain-related vs non-pain-related stimulus in preterm infants.Pain reports · 2025Article
- Automatic pain classification in older patients with hip fracture based on multimodal information fusion.Scientific reports · 2025Article
- Expert consensus on feasibility and application of automatic pain assessment in routine clinical use.Journal of anesthesia, analgesia and critical care · 2025Review
- Personalizing ICU liberation for critically Ill children: shaping the future of the ABCDEF bundle.Current opinion in pediatrics · 2025Review
- Feasibility and Effectiveness of a Low-Code AI Platform for Developing a Neonatal Multimodal Pain Classification Model.Journal of multidisciplinary healthcare · 2025Article
- Artificial intelligence in clinical medicine: a state-of-the-art overview of systematic reviews with methodological recommendations for improved reporting.Frontiers in digital health · 2025Review
- Neonatal Pain Management: Is There An Endocrinal Response?Endocrine, metabolic & immune disorders drug targets · 2025Review
- Applied Artificial Intelligence in Healthcare: A Review of Computer Vision Technology Application in Hospital Settings.Journal of imaging · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo describe the challenges and perspectives of the automation of pain assessment in the Neonatal Intensive Care Unit. DATA SOURCES: A search for scientific articles published in the last 10 years on automated neonatal pain assessment was conducted in the main Databases of the Health Area and Engineering Journal Portals, using the descriptors: Pain Measurement, Newborn, Artificial Intelligence, Computer Systems, Software, Automated Facial Recognition. SUMMARY OF
findingsFifteen articles were selected and allowed a broad reflection on first, the literature search did not return the various automatic methods that exist to date, and those that exist are not effective enough to replace the human eye; second, computational methods are not yet able to automatically detect pain on partially covered faces and need to be tested during the natural movement of the neonate and with different light intensities; third, for research to advance in this area, databases are needed with more neonatal facial images available for the study of computational methods.
conclusionThere is still a gap between computational methods developed for automated neonatal pain assessment and a practical application that can be used at the bedside in real-time, that is sensitive, specific, and with good accuracy. The studies reviewed described limitations that could be minimized with the development of a tool that identifies pain by analyzing only free facial regions, and the creation and feasibility of a synthetic database of neonatal facial images that is freely available to researchers.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.